Modeling the antigen combining site of an anti-dinitrophenyl antibody, ANO2.

A model structure has been constructed for a monoclonal anti-dinitrophenyl antibody. The antibody, ANO2, has been sequenced and cloned (Anglister, J., Frey, T., & McConnell, H.M., 1984, Biochemistry 23, 1138-1142). Its amino acid sequence shows striking homology with the anti-lysozyme Fab fragments HyHel5 (83%) and HyHel10 (73%). Based on this homology, a model for the ANO2 variable heavy and variable light chain framework was constructed using a hybrid of the HyHel5 light chain and the HyHel10 heavy chain backbone, omitting the hypervariable loops. These coordinates were used as scaffolds for the model building of ANO2. The CONGEN conformational sampling algorithm (Bruccoleri, R.E. & Karplus, M., 1987, Biopolymers 26, 127-196) was used to model the six hypervariable loops that contain the antigen-combining site. All the possible conformations of the loop backbones were constructed and the best loop structures were selected using a combination of the CHARMM potential energy function and evaluation of the solvent-accessible surface area of the conformers. The order in which the loops were searched was carried out based on the relative locations of the loops with reference to the framework of the beta-barrel, namely, L2-H1-L3-H2-H3-L1. The model structures thus obtained were compared to the high resolution X-ray structure (Brünger, A.T., Leahy, D.J., Hynes, T.R., & Fox, R.O., 1991, J. Mol. Biol. 221, 239-256).     

Structural model of the anti-snake-toxin antibody,Mα2,3

We present results of structural modeling of the variable fragment of Mα2,3, an antibody capable of neutralizing all short snake toxins. Three different methods were used to model the hypervariable loops: the conformational search algorithm CONGEN (Bruccoleri and Karplus, Biopolymers 26:137–168, 1987), high-temperature molecular dynamics (Bruccoleri and Karplus, Biopolymers 29:1847–1862, 1990), and a combined knowledge-based and energy-based algorithm (Martin et al., Proc. Natl. Acad. Sci. USA 86:9268–9272, 1989). Ninety plausible conformations were generated and were clustered into 13 classes. The clustering results indicate that there was little overlap of the conformational space explored by the different methods. Canonical loop structures were found by all methods for two of the loops, in agreement with previously established empirical modeling criteria. Nine of the 13 classes of structure were rejected on the ground of their lacking common features of antibody combining-site structure. The remaining four models were refined using restrained molecular dynamics. It was found that interconversion between the four resulting structures is possible with no significant energy barriers, suggesting that they are in thermodynamic equilibrium at 300 K. Features of the combining-site structure likely to be particularly important for antigen binding are discussed. © 1996 Wiley-Liss, Inc.     

Ab initio structure prediction of the antibody hypervariable H3 loop

Antibodies have the capability of binding a wide range of antigens due to the diversity of the six loops constituting the complementarity determining region (CDR). Among the six loops, the H3 loop is the most diverse in structure, length, and sequence identity. Prediction of the three‐dimensional structures of antibodies, especially the CDR loops, is an important step in the computational design and engineering of novel antibodies for improved affinity and specificity. Although it has been demonstrated that the conformation of the five non‐H3 loops can be accurately predicted by comparing their sequences against databases of canonical loop conformations, no such connection has been established for H3 loops. In this work, we present the results for ab initio structure prediction of the H3 loop using conformational sampling and energy calculations with the program Prime on a dataset of 53 loops ranging in length from 4 to 22 residues. When the prediction is performed in the crystal environment and including symmetry mates, the median backbone root mean square deviation (RMSD) is 0.5 Å to the crystal structure, with 91% of cases having an RMSD of less than 2.0 Å. When the prediction is performed in a noncrystallographic environment, where the scaffold is constructed by swapping the H3 loops between homologous antibodies, 70% of cases have an RMSD below 2.0 Å. These results show promise for ab initio loop predictions applied to modeling of antibodies. © 2012 Wiley Periodicals, Inc.     

Toward high‐resolution homology modeling of antibody Fv regions and application to antibody–antigen docking

High‐resolution homology models are useful in structure‐based protein engineering applications, especially when a crystallographic structure is unavailable. Here, we report the development and implementation of RosettaAntibody, a protocol for homology modeling of antibody variable regions. The protocol combines comparative modeling of canonical complementarity determining region (CDR) loop conformations and de novo loop modeling of CDR H3 conformation with simultaneous optimization of V_L‐V_H rigid‐body orientation and CDR backbone and side‐chain conformations. The protocol was tested on a benchmark of 54 antibody crystal structures. The median root mean square deviation (rmsd) of the antigen binding pocket comprised of all the CDR residues was 1.5 Å with 80% of the targets having an rmsd lower than 2.0 Å. The median backbone heavy atom global rmsd of the CDR H3 loop prediction was 1.6, 1.9, 2.4, 3.1, and 6.0 Å for very short (4–6 residues), short (7–9), medium (10–11), long (12–14) and very long (17–22) loops, respectively. When the set of ten top‐scoring antibody homology models are used in local ensemble docking to antigen, a moderate‐to‐high accuracy docking prediction was achieved in seven of fifteen targets. This success in computational docking with high‐resolution homology models is encouraging, but challenges still remain in modeling antibody structures for sequences with long H3 loops. This first large‐scale antibody–antigen docking study using homology models reveals the level of “functional accuracy” of these structural models toward protein engineering applications. Proteins 2009; 74:497–514. © 2008 Wiley‐Liss, Inc.     

Refining homology models by combining replica-exchange molecular dynamics and statistical potentials

A protocol is presented for the global refinement of homology models of proteins. It combines the advantages of temperature-based replica-exchange molecular dynamics (REMD) for conformational sampling and the use of statistical potentials for model selection. The protocol was tested using 21 models. Of these 14 were models of 10 small proteins for which high-resolution crystal structures were available, the remainder were targets of the recent CASPR exercise. It was found that REMD in combination with currently available force fields could sample near-native conformational states starting from high-quality homology models. Conformations in which the backbone RMSD of secondary structure elements (SSE-RMSD) was lower than the starting value by 0.5-1.0 A were found for 15 out of the 21 cases (average 0.82 A). Furthermore, when a simple scoring function consisting of two statistical potentials was used to rank the structures, one or more structures with SSE-RMSD of at least 0.2 A lower than the starting value was found among the five best ranked structures in 11 out of the 21 cases. The average improvement in SSE-RMSD for the best models was 0.42 A. However, none of the scoring functions tested identified the structures with the lowest SSE-RMSD as the best models although all identified the native conformation as the one with lowest energy. This suggests that while the proposed protocol proved effective for the refinement of high-quality models of small proteins scoring functions remain one of the major limiting factors in structure refinement. This and other aspects by which the methodology could be further improved are discussed.     

Application of a directed conformational search for generating 3-D coordinates for protein structures from alpha-carbon coordinates.

A directed conformational search algorithm using the program CONGEN (ref. 3), which samples backbone conformers, is described. The search technique uses information from the partially built structures to direct the search process and is tested on the problem of generating a full set of backbone Cartesian coordinates given only alpha-carbon coordinates. The method has been tested on six proteins of known structure, varying in size and classification, and was able to generate the original backbone coordinates with RMSs ranging from 0.30-0.87A for the alpha-carbons and 0.5-0.99A RMSs for the backbone atoms. Cis peptide linkages were also correctly identified. The procedure was also applied to two proteins available with only alpha-carbon coordinates in the Brookhaven Protein Data Bank; thioredoxin (SRX) and triacylglycerol acylhydrolase (TGL). All-atom models are proposed for the backbone of both these proteins. In addition, the technique was applied to randomized coordinates of flavodoxin to assess the effects of irregularities in the data on the final RMS. This study represents the first time a deterministic conformational search was used on such a large scale.     

Alignment algorithm for homology modeling and threading.

A DNA/protein sequence comparison is a popular computational tool for molecular biologists. Finding a good alignment implies an evolutionary and/or functional relationship between proteins or genomic loci. Sequential similarity between two proteins indicates their structural resemblance, providing a practical approach for structural modeling, when structure of one of these proteins is known. The first step in the homology modeling is a construction of an accurate sequence alignment. The commonly used alignment algorithms do not provide an adequate treatment of the structurally mismatched residues in locally dissimilar regions. We propose a simple modification of the existing alignment algorithm which treats these regions properly and demonstrate how this modification improves sequence alignments in real proteins.     

Low-mode docking search in iGluR homology models implicates three residues in the control of ligand selectivity

Homology models of the ionotropic rat kainate receptor iGluR6, based on the ligand binding domains of iGluR2, were constructed. A systematic analysis by low-mode docking searches of kainic acid in homology models of the native iGluR6 receptor, chimeric (iGluR2 and iGluR6) receptors and mutant receptors have identified three residues which influence the conformation of kainic acid in the binding core and hence the affinity for kainic acid. These residues are Leu650, Thr649 and Leu704, all located in domain 2. Leu650 has previously been implicated in the control of selectivity of iGluR2. However, this is the first report that suggests that Thr649 and Leu704 play a role in receptor selectivity.     

Affinity maturation of a novel antagonistic human monoclonal antibody with a long VH CDR3 targeting the Class A GPCR formyl-peptide receptor 1

Therapeutic monoclonal antibodies targeting G-protein-coupled receptors (GPCRs) are desirable for intervention in a wide range of disease processes. The discovery of such antibodies is challenging due to a lack of stability of many GPCRs as purified proteins. We describe here the generation of Fpro0165, a human anti-formyl peptide receptor 1 (FPR1) antibody generated by variable domain engineering of an antibody derived by immunization of transgenic mice expressing human variable region genes. Antibody isolation and subsequent engineering of affinity, potency and species cross-reactivity using phage display were achieved using FPR1 expressed on HEK cells for immunization and selection, along with calcium release cellular assays for antibody screening. Fpro0165 shows full neutralization of formyl peptide-mediated activation of primary human neutrophils. A crystal structure of the Fpro0165 Fab shows a long, protruding V_H CDR3 of 24 amino acids and in silico docking with a homology model of FPR1 suggests that this long V_H CDR3 is critical to the predicted binding mode of the antibody. Antibody mutation studies identify the apex of the long V_H CDR3 as key to mediating the species cross-reactivity profile of the antibody. This study illustrates an approach for antibody discovery and affinity engineering to typically intractable membrane proteins such as GPCRs.     

Affinity maturation of a novel antagonistic human monoclonal antibody with a long VH CDR3 targeting the Class A GPCR formyl-peptide receptor 1

Therapeutic monoclonal antibodies targeting G-protein-coupled receptors (GPCRs) are desirable for intervention in a wide range of disease processes. The discovery of such antibodies is challenging due to a lack of stability of many GPCRs as purified proteins. We describe here the generation of Fpro0165, a human anti-formyl peptide receptor 1 (FPR1) antibody generated by variable domain engineering of an antibody derived by immunization of transgenic mice expressing human variable region genes. Antibody isolation and subsequent engineering of affinity, potency and species cross-reactivity using phage display were achieved using FPR1 expressed on HEK cells for immunization and selection, along with calcium release cellular assays for antibody screening. Fpro0165 shows full neutralization of formyl peptide-mediated activation of primary human neutrophils. A crystal structure of the Fpro0165 Fab shows a long, protruding V_H CDR3 of 24 amino acids and in silico docking with a homology model of FPR1 suggests that this long V_H CDR3 is critical to the predicted binding mode of the antibody. Antibody mutation studies identify the apex of the long V_H CDR3 as key to mediating the species cross-reactivity profile of the antibody. This study illustrates an approach for antibody discovery and affinity engineering to typically intractable membrane proteins such as GPCRs.     

Modeling the structure of Pyrococcus furiosus rubredoxin by homology to other X-ray structures.

The three-dimensional structure of rubredoxin from the hyperthermophilic archaebacterium, Pyrococcus furiosus, has been modeled from the X-ray crystal structures of three homologous proteins from Clostridium pasteurianum, Desulfovibrio gigas, and Desulfovibrio vulgaris. All three homology models are similar. When comparing the positions of all heavy atoms and essential hydrogen atoms to the recently solved crystal structure (Day, M. W., et al., 1992, Protein Sci. 1, 1494-1507) of the same protein, the homology model differ from the X-ray structure by 2.09 A root mean square (RMS). The X-ray and the zinc-substituted NMR structures (Blake, P. R., et al., 1992b, Protein Sci. 1, 1508-1521) show a similar level of difference (2.05 A RMS). On average, the homology models are closer to the X-ray structure than to the NMR structures (2.09 vs. 2.42 A RMS).     

Study of the Villin headpiece folding dynamics by combining coarse-grained Monte Carlo evolution and all-atom molecular dynamics

The folding mechanism of the Villin headpiece (HP36) is studied by means of a novel approach which entails an initial coarse-grained Monte Carlo (MC) scheme followed by all-atom molecular dynamics (MD) simulations in explicit solvent. The MC evolution occurs in a simplified free-energy landscape and allows an efficient selection of marginally-compact structures which are taken as viable initial conformations for the MD. The coarse-grained MC structural representation is connected to the one with atomic resolution through a "fine-graining" reconstruction algorithm. This two-stage strategy is used to select and follow the dynamics of seven different unrelated conformations of HP36. In a notable case the MD trajectory rapidly evolves towards the folded state, yielding a typical root-mean-square deviation (RMSD) of the core region of only 2.4 A from the closest NMR model (the typical RMSD over the whole structure being 4.0 A). The analysis of the various MC-MD trajectories provides valuable insight into the details of the folding and mis-folding mechanisms and particularly about the delicate influence of local and nonlocal interactions in steering the folding process.     

Mitigation of reversible self-association and viscosity in a human IgG1 monoclonal antibody by rational,structure-guided Fv engineering

Undesired solution behaviors such as reversible self-association (RSA), high viscosity, and liquid-liquid phase separation can introduce substantial challenges during development of monoclonal antibody formulations. Although a global mechanistic understanding of RSA (i.e., native and reversible protein-protein interactions) is sufficient to develop robust formulation controls, its mitigation via protein engineering requires knowledge of the sites of protein-protein interactions. In the study reported here, we coupled our previous hydrogen-deuterium exchange mass spectrometry findings with structural modeling and in vitro screening to identify the residues responsible for RSA of a model IgG1 monoclonal antibody (mAb-C), and rationally engineered variants with improved solution properties (i.e., reduced RSA and viscosity). Our data show that mutation of either solvent-exposed aromatic residues within the heavy and light chain variable regions or buried residues within the heavy chain/light chain interface can significantly mitigate RSA and viscosity by reducing the IgG's surface hydrophobicity. The engineering strategy described here highlights the utility of integrating complementary experimental and in silico methods to identify mutations that can improve developability, in particular, high concentration solution properties, of candidate therapeutic antibodies.     

A critical assessment of the topomer search model of protein folding using a continuum explicit-chain model with extensive conformational sampling

Recently, a series of closely related theoretical constructs termed the "topomer search model" (TSM) has been proposed for the folding mechanism of small, single-domain proteins. A basic assumption of the proposed scenarios is that the rate-limiting step in folding is an essentially unbiased, diffusive search for a conformational state called the native topomer defined by an overall native-like topological pattern. Successes in correlating TSM-predicted folding rates with that of real proteins have been interpreted as experimental support for the model. To better delineate the physics entailed, key TSM concepts are examined here using extensive Langevin dynamics simulations of continuum C(alpha) chain models. The theoretical native topomers of four experimentally well-studied two-state proteins are characterized. Consistent with the TSM perspective, we found that the sizes of the native topomers increase with experimental folding rate. However, a careful determination of the corresponding probabilities that the native topomers are populated during a random search fails to reproduce the previously predicted folding rates. Instead, our results indicate that an unbiased TSM search for the native topomer amounts to a Levinthal-like process that would take an impossibly long average time to complete. Furthermore, intraprotein contacts in all four native topomers considered exhibit no apparent correlation with the experimental phi-values determined from the folding kinetics of these proteins. Thus, the present findings suggest that certain basic, generic yet essential energetic features in protein folding are not accounted for by TSM scenarios to date.     

Study of conformational rearrangement and refinement of structural homology models by the use of heteronuclear dipolar couplings

For an increasing fraction of proteins whose structures are being studied, sequence homology to known structures permits building of low resolution structural models. It is demonstrated that dipolar couplings, measured in a liquid crystalline medium, not only can validate such structural models, but also refine them. Here, experimental ¹H-¹⁵N, ¹H-¹³C, and ¹³C-¹³C dipolar couplings are shown to decrease the backbone rmsd between various homology models of calmodulin (CaM) and its crystal structure. Starting from a model of the Ca²⁺-saturated C-terminal domain of CaM, built from the structure of Ca²⁺-free recoverin on the basis of remote sequence homology, dipolar couplings are used to decrease the rmsd between the model and the crystal structure from 5.0 to 1.25 Å. A better starting model, built from the crystal structure of Ca²⁺-saturated parvalbumin, decreases in rmsd from 1.25 to 0.93 Å. Similarly, starting from the structure of the Ca²⁺-ligated CaM N-terminal domain, experimental dipolar couplings measured for the Ca²⁺-free form decrease the backbone rmsd relative to the refined solution structure of apo-CaM from 4.2 to 1.0 Å.     

Molecular modeling of cardiac glycoside binding by the human sequence monoclonal antibody 1B3

The amino acid sequences of the heavy- and light-chain variable regions of the high-affinity human sequence antidigoxin monoclonal antibody 1B3 (mAb 1B3) were determined, and a structural model for the mAb's variable region was developed by homology modeling techniques. The structural model provided the basis for computationally docking digoxin and eight related cardiac glycosides into the putative binding site of mAb 1B3. Analysis of the consensus binding mode obtained for digoxin showed that the cardenolide moiety of digoxin is deeply embedded in a predominantly hydrophobic, narrow cavity, whereas the terminal, gamma-carbohydrate group is solvent-exposed. The docking results indicated that the primary driving forces for digoxin binding by mAb 1B3 are hydrophobic interactions with the digoxin steroid ring system and hydrogen bonds with the digitoxose groups. The binding model accounts for the experimentally observed variations in mAb 1B3 binding affinity for various structural analogs of digoxin used previously to develop a 3D structure-activity relationship model of drug binding (Farr CD, Tabet MR, Ball WJ Jr, Fishwild DM, Wang X, Nair AC, Welsh WJ. Three-dimensional quantitative structure-activity relationship analysis of ligand binding to human sequence antidigoxin monoclonal antibodies using comparative molecular field analysis. J Med Chem 2002;45:3257-3270). In particular, the hydrogen bond pattern is consistent with the unique sensitivity of mAb 1B3's binding affinity to the number of sugar residues present in a cardiac glycoside. The hydrophobic environment about the steroid moiety of digoxin is compatible with the mAb's reduced affinity for ligands that possess hydrophilic hydroxyl and acetyl group modifications in this region. The model also indicated that most of the amino acid residues in contact with the ligand reside in or about the three complementarity determining regions (CDRs) of the heavy chain and the third CDR of the light chain. A comparison of the 1B3 binding model with the crystal structures of two murine antidigoxin mAbs revealed similar binding patterns used by the three mAbs, such as a high frequency of occurrence of aromatic, hydrophobic residues in the CDRs and a dominant role of the heavy chain CDR3 in antigen binding.     

The structure of serine hydroxymethyltransferase as modeled by homology and validated by site-directed mutagenesis.

We describe a model for the three-dimensional structure of E. coli serine hydroxymethyltransferase based on its sequence homology with other PLP enzymes of the alpha-family and whose tertiary structures are known. The model suggests that certain amino acid residues at the putative active site of the enzyme can adopt specific roles in the catalytic mechanism. These proposals were supported by analysis of the properties of a number of site-directed mutants. New active site features are also proposed for further experimental testing.     

Fast and simple Monte Carlo algorithm for side chain optimization in proteins: application to model building by homology.

An unknown protein structure can be predicted with fair accuracy once an evolutionary connection at the sequence level has been made to a protein of known 3-D structure. In model building by homology, one typically starts with a backbone framework, rebuilds new loop regions, and replaces nonconserved side chains. Here, we use an extremely efficient Monte Carlo algorithm in rotamer space with simulated annealing and simple potential energy functions to optimize the packing of side chains on given backbone models. Optimized models are generated within minutes on a workstation, with reasonable accuracy (average of 81% side chain chi 1 dihedral angles correct in the cores of proteins determined at better than 2.5 A resolution). As expected, the quality of the models decreases with decreasing accuracy of backbone coordinates. If the back-bone was taken from a homologous rather than the same protein, about 70% side chain chi 1 angles were modeled correctly in the core in a case of strong homology and about 60% in a case of medium homology. The algorithm can be used in automated, fast, and reproducible model building by homology.     

Improving the solubility of anti‐LINGO‐1 monoclonal antibody Li33 by isotype switching and targeted mutagenesis

Monoclonal antibodies (Mabs) are a favorite drug platform of the biopharmaceutical industry. Currently, over 20 Mabs have been approved and several hundred others are in clinical trials. The anti‐LINGO‐1 Mab Li33 was selected from a large panel of antibodies by Fab phage display technology based on its extraordinary biological activity in promoting oligodendrocyte differentiation and myelination in vitro and in animal models of remyelination. However, the Li33 Fab had poor solubility when converted into a full antibody in an immunoglobulin G1 framework. A detailed analysis of the biochemical and structural features of the antibody revealed several possible reasons for its propensity to aggregate. Here, we successfully applied three molecular approaches (isotype switching, targeted mutagenesis of complementarity determining region residues, and glycosylation site insertion mutagenesis) to address the solubility problem. Through these efforts we were able to improve the solubility of the Li33 Mab from 0.3 mg/mL to >50 mg/mL and reduce aggregation to an acceptable level. These strategies can be readily applied to other proteins with solubility issues.     

Predicting the Structure of the Flavodoxin from Eschericia coli by Homology Modeling,Distance Geometry and Molecular Dynamics

Abstract

As part of our on-going development of a method, based upon distance geometry calculations, for predicting the structures of proteins from the known structures of their homologues, we have predicted the structure of the 176 residue Flavodoxin from Escherichia coli. This prediction was based upon the crystal structures of the homologous Flavodoxins from Anacystis nidulans, Chondrus crispus, Desulfovibrio vulgaris and Clostridium beijerinckii, whose sequence identities with Escherichia coli were 44%, 33%, 23% and 16%, respectively. A total of 13,043 distance constraints among the alpha-carbons of the Escherichia coli structure were derived from the sequence alignments with the known structures, together with 8,893 distance constraints among backbone and sidechain atoms of adjacent residues, 978 between the alpha-carbons and selected atoms of the flavin mononucleotide cofactor, 116 constraints to enforce conserved hydrogen bonds, and 452 constraints on the torsion angles in conserved residues. An ensemble of ten random Escherichia coli structures was computed from these constraints, with an average root mean square coordinate deviation (RMSD) among the alpha carbons of 0.85 Ångstroms (excluding the first 1 and last 6 residues, which have no corresponding residues in any of the homologues and hence were unconstrained); the corresponding average heavy-atom RMSD was 1.60 Å.

Since the distance geometry calculations were performed without hydrogen atoms, protons were added to the resulting structures and these structures embedded in a 50 × 50 × 40 Å solvent box with periodic boundary conditions. They were then subjected to a 20 picosecond dynamical simulated annealing procedure, starting at 300 K and gradually reduced to 10K, in which all the distance and torsion angle constraints were maintained by means of harmonic restraint functions. This was followed up by 1000 iterations of unrestrained conjugate gradients minimization. The goal of this energy refinement procedure was not to drastically modify the structures in an attempt at a priori prediction, but merely to improve upon the predictions obtained from the geometric constraints, particularly with regard to their local backbone and sidechain conformations and their hydrogen bonds. The resulting structures differed from the respective starting structures by an average of 1.52 Å in their heavy atom RMSD's, while the average RMSD among the heavy atoms of residues 2-170 increased slightly to 1.66 Å. We hope these structures will be good enough to enable the phase problem to be solved for the crystallographic data that is now being collected on this protein.